Modeling and Planning Multimodal Transport Paths for Risk and Energy Efficiency Using AND/OR Graphs and Discrete Ant Colony Optimization

Abstract

Path sequence selection is important for multimodal transport processes. AND/OR graphs (AOG) have been applied to describe practical multimodal transport route planning problems by using ‘AND’ and ‘OR’ matrices. An AOG-based multimodal transport route planning problem is an NP-hard combinatorial optimization problem. Heuristic evolution methods can be adopted to handle it. While adjacency (AND) relationship issues can be addressed, contradiction (OR) relations are not well addressed by existing multimodal transport route planning methods. Thus, an ineffective result may be obtained in practice. The OR matrix is a conflict matrix that describes the choice of mode of transport in the process of multimodal transport. By using a contradiction matrix together with an adjacency matrix and tabu list, an approach used in existing work, this paper proposes an effective triple-phase generate route method (TPGR) to produce a feasible multimodal transport path sequence based on an AOG. This paper uses energy consumption to evaluate the multimodal transport energy efficiency. The information entropy is applied to describe the risks of the transport process. The energy consumption and the information entropy lead to a novel dual-objective optimization model where route energy consumption and route risk are minimized. An improved ant colony algorithm is developed to effectively generate a set of Pareto solutions for route selection, which are used for the dual-objective multimodal transport route optimization problem. This methodology is applied to practical multimodal transport route selection processes on two maps to verify its effectiveness and feasibility.

Keywords

• Multimodal transport
• AND/OR graph
• dual-objective discrete ant colony optimization
• modeling and simulation